Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2020 Dec 19.
Published in final edited form as: J Phys Chem B. 2019 Dec 11;123(50):10709–10717. doi: 10.1021/acs.jpcb.9b09352

Coaction of Electrostatic and Hydrophobic Interactions: Dynamic Constraints on Disordered TrkA Juxtamembrane Domain

Zichen Wang †,§, Huaxun Fan ‡, Xiao Hu #, John Khamo ‡, Jiajie Diao #,*, Kai Zhang ‡,&,^,*, Taras V Pogorelov †,&,§,^,*
PMCID: PMC7162675  NIHMSID: NIHMS1570259  PMID: 31751135

Abstract

In the receptor tyrosine kinase family, conformational change induced by ligand binding is transmitted across membrane via a single transmembrane helix and a flexible juxtamembrane domain (JMD). Membrane dynamics makes it challenging to study the structural mechanism of receptor activation experimentally. In this study, we employ all-atom molecular dynamics with Highly Mobile Membrane-Mimetic to capture the native conformation of the JMD in tropomyosin receptor kinase A (TrkA). We find that PIP2 lipids engage in stable binding with multiple basic residues. Anionic lipids can compete with salt bridges within the peptide and alter TrkA-JMD conformation. We discover three-residue JMD insertion into the membrane, and are able to either enhance or reduce the level of insertion through computationally-designed point mutations. Vesicle-binding experiment supports computational results, and indicates that hydrophobic insertion is comparable to electrostatic binding for membrane anchoring. Biochemical assays on cell-lines with mutated TrkA shows that enhanced TrkA-JMD insertion promotes receptor ubiquitination but does not affect signaling capacity. Our joint work points to a scenario where lipid headgroups and tails respectively interact with basic and hydrophobic residues on disorder domain, restraining flexibility and potentially modulating protein function.

Graphical Abstract

graphic file with name nihms-1570259-f0001.jpg

Introduction

Effective transmembrane signaling is vital to cellular decision-making. The family of receptor tyrosine kinase (RTK) contains 58 membrane proteins that dimerize upon ligand binding, induce autophosphorylation in the intracellular kinase domain, and activate downstream cascades that affect cell proliferation and function. RTK can be structurally divided into extracellular kinase ligand-binding ectodomain, single-pass transmembrane domain (TMD), short intracellular juxtamembrane domain (JMD), and intracellular kinase domain (Figure 1).1 RTKs have adopted a complex regulatory role in signaling cascades1 and are subject to transactivation by other receptors, e.g., G-protein coupled receptors.2

Figure 1.

Figure 1.

Open in a new tab

Overview of the system. a) Schematic drawing of RTK dimers upon ligand binding. Domains not modeled are greyed out. (b) A snapshot of the modeled system: lipids and peptide are color-coded by type; HMMM solvent DCLE is in brown.

Experimental studies have assigned unique functions to the JMD3,4, which can form secondary structures or be disordered. In particular, the JMD of the epidermal growth factor receptor (EGFR) can form a membrane-anchored helix or be part of a free antiparallel helix dimer, to favor the inactive or active state, respectively.5,6 In the fibroblast growth factor receptor 3 (FGFR3), a disordered JMD is released from being embedded in the membrane upon rotation of TMD by activating mutations.7 JMD in some RTKs can also stabilize unliganded dimer8, or serve as docking site for other cellular proteins.9

Common in these studies is the interplay between JMD and cytoplasmic membrane. An extensive computational study10 of all RTK JMDs reveals that the conserved positively-charged JMD N-terminus actively interacts with anionic lipids such as phosphatidylinositol 4,5-bisphosphate (PIP2). The JMDs can sequester PIP2, effectively modifying local membrane environment.11–13 Moreover, PIP2-JMD interaction has been shown to modulate receptor activity of EGFR.14

Tropomyosin receptor kinase A (TrkA) is well-studied for its role in neuronal differentiation and synapse plasticity,15 but little structural information is known regarding the activation mechanism. Deletion of a conserved Lys-Phe-Gly patch in TrkA-JMD impacts signaling activity and receptor turnover, hinting at the significance of this flexible region.16

Mechanistically, upon ligand binding a conformational change is propagated from ectodomain to TMD, which by employing JMD as a flexible fulcrum, reorients the kinase domain for autophosphorylation. It is still largely unknown how this short, intrinsically disordered JMD region transduces structural change in a controlled manner. Here, we study the native conformation and membrane-protein interaction of TrkAJMD using all-atom molecular dynamics (MD) with the Highly Mobile Membrane-Mimetic model (HMMM)17–19 and matching experiments. TMD and kinase domain are truncated at this stage to reduce drag and improve sampling, as well as to avoid additional variables. The characterization of isolated JMD will be the first step towards a mechanistic understanding of the conformational coupling between TMD rotation and kinase activation in TrkA.

Methods

Molecular Dynamics Simulation

Structure Preparation.

The wild-type sequence of human-TrkA was obtained from the UniProt Knowledgebase.20 The JMD sequence was taken as the 26 amino acids C-terminus of the transmembrane domain, to be residues 440–465. The coordinate files for the wild type and three mutants were assembled using Avogadro software,21 then solvated in VMD and simulated for 5 ns for equilibration.

System Assembly.

Complete peptide-membrane systems were generated using webserver CHARMM-GUI.22 Charge-neutral ACE and CT2 terminus patches were applied to the peptide. Equilibrated peptide was placed parallel and 20 Å away from the membrane (Figure 1b). Membrane was built with HMMM Membrane Builder.23 The HMMM shortens the full-length lipid tails and fills the membrane core with an organic solvent which raises lipid lateral diffusion by ten-fold, allowing enhanced conformation sampling. Lipid area scaling factor is set at 1.1, and terminal acyl carbon number at 6. Phosphatidylcholine (PC), phosphatidylserine (PS) and phosphatidylinositol 4,5-bisphosphate (PIP2) are incorporated. Three membrane compositions were designed to explore the roles of different lipids, while mimicking the mammalian membrane.24,25 Numbers of PC:PS:PIP2 per leaflet were 59:0:0 for PC membrane, 40:20:0 for PC/PS membrane, 41:12:6 for PC/PS/PIP2 membrane. Membrane x-/y-dimensions of the systems were maintained at 65 Å × 65 Å, and z-dimension at 120 Å. Extended z-dimension shields charges from the other periodic membrane leaflet. Neutralizing potassium or chloride ions were added (3 chloride ions for PC, 37 potassium ions for PC/PS, 69 potassium ions for PC/PS/PIP2). Each replicate has around 45,000 atoms. For statistics, 5 replicates were made for each lipid composition and JMD peptide variant (WT, dKFG, FS, RW), totaling 60 replicates (Table S2). Each replicate was individually generated from CHARMM-GUI with randomization in initial configuration of lipids for better sampling.

Simulation Run.

All simulations were performed using software NAMD2.26 Lipids, ions, and peptides were modeled with CHARMM36m force field refined for disordered proteins,27 water molecules with the TIP3P model,28 and DCLE molecules with CGenFF.29 A restraint of 1 kcal mol−1 Å−2 perpendicular to membrane plane was applied to the carboxyl carbon atoms of each lipid tail to avoid short-tail HMMM lipids partitioning into the solution. The restraint allowed for ±3.5 Å vertical motion along the z-direction. The lateral motions of lipids were free of restraints. Short-range electrostatics and Van der Waals interactions were set with cutoff 12 Å with switching at 10 Å. Long-range electrostatics was modeled by the Particle Mesh Ewald method with 1 Å grid spacing.30,31 SETTLE algorithm was used to restrain the hydrogen-atom bond length.32 NPT ensemble was chosen. The temperature was controlled at 303 K and the pressure was controlled at 1 atm by Langevin dynamics.33 The integration step was set at 2 fs. All equilibration before the production followed the 6 cycles suggested by CHARMM-GUI where force constants were gradually reduced. Each replicate was simulated for 200 ns, reaching a total of 12 μs modeling time.

Convergence Test.

To validate the use of HMMM, we converted one randomly chosen WT replicate from each membrane composition to full-tail membrane system (lipid tail types are 16:0/18:1Δ9), and simulated for 100 ns. The insertion distance, an informative metric (see Results and Discussion), for three reporter residues that are located on regions of the peptide with distinct insertion profiles, was plotted for the combined trajectory (Figure 2). The partitioning of peptide is largely consistent between HMMM and full-tail membrane. For additional control, the same three replicates with HMMM membrane were extended to 300 ns (Figure S1). Z-positions of the reporter residues in the extended simulations fluctuate around the same mean as in the initial 200 ns simulations, suggesting the systems were equilibrated. Root-mean-square fluctuation (RMSF) of all residues at sliding time windows confirmed that after 50 ns, relatively low RMSFs of ~3 Å were sustained for membrane-contacting residues (Figure S2). All analyses in Results and Discussion were performed in the 100–200 ns interval.

Figure 2.

Figure 2.

Open in a new tab

Comparison between the WT residue partitioning in HMMM and full-tail membrane for a) PC, b) PC/PS, c) PC/PS/PIP2 membrane. Arg444, Ile450, and Leu456 are chosen for their distinct insertion profiles, as characterized in Results and Discussion. Insertion distance is calculated as the z-axis difference between whole residue center of mass and the average position of glycerol phosphorus atoms (horizontal dashed line). Positive value corresponds to membrane insertion.

Trajectory Analysis.

All trajectories were visually inspected in VMD.34 Analyses were written using MDAnalysis.35 Details can be found in Supporting Information.

Peptide-Vesicle Binding Experiment

Vesicle Synthesis.

Vesicles with different compositions were synthesized according to established protocols.36 Glass vials and glass syringes were washed three times with Milli-Q water, ethanol (100%, Fisher Scientific, USA) and chloroform (Fisher Scientific, USA) before use. Lipids (Avanti Polar Lipids, Inc, USA) were added into the cleaned glass vial by the glass syringe and dried under vacuum overnight. The glass vial was wrapped with alumina foil with a small hole on the top. Upon drying, the formed film on the glass vial was dissolved with 200 μL of 50 mM tris buffered saline (pH 8.0). The synthesized vesicle was diluted to designated concentrations and sonicated by an ultrasonic liquid processor (Misonix, USA) for 2 min (amplitude: 10%, process time: 2 s, and quiet time: 4 s).

Slide Preparation.

The quartz slides (with drilled holes, 1 inch × 3 inch, 1 mm thick, Finkenbeiner Inc, USA) and the cover slides (24 mm × 40 mm, Corning, USA) were coated with biotin-polyethylene glycol (biotin-PEG) and PEG in order to eliminate nonspecific binding of vesicles, as well as to generate biotin-NeutrAvidin bridges on the surface. The biotin-PEG and PEG were covalently immobilized onto the slide’s surface according to the established protocol.37 Briefly, the slides were thoroughly cleaned with household detergent, MilliQ water, acetone (Fisher Scientific, USA), 1 M potassium hydroxide (Fisher Scientific, USA) and methanol (99.8%, Fisher Scientific, USA) for 1 h each. Each quartz slide was burnt with a propane torch, incubated in methanol containing with 1% (v/v) 3-Aminopropyltriethoxysilane (APTES, Sigma, USA) and 5% (v/v) acetone, and coated with m-PEG-SVA and biotin-PEG-SVA (Laysan Bio Inc, USA). The flow chamber was assembled from the biotin-PEG coated quartz slide and a cover slide using double-sided tape and epoxy glue.

Sample Immobilization.

Incubate 50 μL of 0.1 mg/mL NeutrAvidin (Fisher Scientific, USA) in the channels for 5 min at room temperature, followed by a thorough washing of the unbound NeutrAvidin. Incubate 50 μL of vesicles in the channel for 30 min at room temperature and wash out unbound vesicles with 200 μL T50. Inject 50 μL of Cy3 labeled RW, FS or WT peptides (78.0%, 90.0% and 75.3%, Genscript, China) into the channel and incubate for 15 min at room temperature and thoroughly wash out unbound peptides with 200 μL T50 buffer. Before imaging, 50 μL of oxygen scavenger solution (0.1 mg/mL glucose oxidase (Sigma, USA), 0.02 mg/mL catalase (Sigma, USA) and 0.8% (w/w) dextrose (Sigma, USA), 3 mM 6-hydroxy-2,5,7,8-tetramethyl-chroman-2-carboxylic acid (Trolox, Sigma, USA)) was injected into each channel to eliminate single-molecule blinking.

Single-molecule Imaging.

The binding events between the vesicles and the peptides were recorded with Total Internal Reflection Fluorescence Microscopy (TIRF) microscopy. DiD-labeled vesicles were excited at 633 nm and the Cy3 labeled peptides were excited at 532 nm. Twenty frames of image stack propane with 200 ms exposure time. Real-time image analysis was done using the custom software obtained from Dr. Taekjip Ha’s group at Johns Hopkins University.

Immunoblot Experiment

Cell Culture and Transfection.

SH-SY5Y cells were cultured in DMEM/F12K 50/50 medium supplemented with 10% FBS, and 1× Penicillin-Streptomycin solution (complete medium) in 35 mm dish. Cultures were maintained in a standard humidified incubator at 37°C with 5% CO2. For Western blots, 600 ng of DNA was combined with 1.8 ul Turbofect in 60 ul of serum-free DMEM/F12K 50/50. The transfection mixtures were incubated at room temperature for 20 minutes prior to adding to cells cultured in 35 mm dishes with 2 mL complete medium. The transfection medium was replaced with 2 mL complete medium after 3 hours of transfection to recover cells overnight. As for HEK293T cells, the medium for culture was DMEM supplemented with 10% FBS, and 1× Penicillin-Streptomycin solution (complete medium), transfection mixtures were made with serum-free DMEM.

Western Blot.

SH-SY5Y Cells were washed once with 1 mL cold DPBS and changed to 1 mL serum-free DMEM/F12K 50/50 medium with 1× Penicillin-Streptomycin solution to minimize the base-level ERK activation induced by serum. After starvation for 5 hours, 20 μg Cycloheximide was added directly to the medium and incubated for 1 h before NGF stimulation (1000 ng/mL final concentration). Cells were then lysed with 100 μL cold lysis buffer (RIPA + protease/phosphatase cocktail) at 0, 10, 90, 180 minutes. Lysates were centrifuged at 17,000 RCF for 10 min at 4°C and the suspension was collected. Purified lysates were normalized using the Bradford reagent (Thermo Fisher Scientific #23238). Equal amount of samples was mixed with LDS buffer and loaded onto 10% or 12% polyacrylamide gels. SDS-PAGE was performed at room temperature with cold water bath. Samples were transferred to PVDF membranes at 30 V overnight or 80 V for 90 min at 4°C. Membranes were blocked in 5% BSA/TBST for 1 h at room temperature and probed with the primary and secondary antibodies according to manufacturer’s protocol. Membranes were incubated with ECL substrate and imaged using a Bio-Rad ChemiDoc XRS chemiluminescence detector (BioRad). As for HEK293T cells, serum-free DMEM with 1× Penicillin-Streptomycin solution was used for starvation, and all the rest procedure was the same.

Quantification of Protein Level.

The band intensity was analyzed by ImageJ. The level of HA-TrkA and pERK was normalized with the intensity of GAPDH in each lane. Student t-test was done using Graphpad Prism.

Results and Discussion

Hydrophobic Interactions

To probe the conformations of TrkA-JMD bound to different membranes, we calculated the distances between the membrane closer to the peptide and the center of mass of each residue (Figure 3 - PC/PS; Figure S3, S4 - PC, PC/PS/PIP2). Membrane position is determined by the average z-position of lipid glycerol phosphorus atoms. Basic residues (blue) in the N-terminus (left in Figure 3a) predominantly interact with lipid head groups, as evidenced by their partitioning just below the glycerol phosphorus atoms. However, in all three membrane types, residues Phe448, Gly449, Ile450 are partitioned beyond the head-water interfacial region and caged by the edge of hydrocarbon tails. This behavior is defined as membrane insertion in further discussion. Residues C-terminal (right in Figure 3a) to Arg452 barely interact with the membrane and are suspended in water. The broad interquartile range for residues on the C-terminus indicates high flexibility caused by the truncation of the kinase domain as well as the inability to insert. The insertion distance plot can be visualized as the ensemble-average conformation relative to membrane, which resembles the actual structure (Figure 3b) and offers information on the degree of fluctuation.

Figure 3.

Figure 3.

Open in a new tab

TrkA-JMD insertion into the membrane. (a) Insertion distance is calculated as the z-axis difference between whole residue center of mass and the average position of glycerol phosphorus atoms (horizontal dashed line) in PC/PS membrane. Points are represented by boxplot and three quartiles are shown. Boxes and the sequence are color-coded by residue type: yellow - hydrophobic, grey - polar, blue - basic, and red - acidic. (b) A snapshot of peptide insertion: membrane core is on the top; phosphorus atoms are grey spheres.

To investigate the significance of hydrophobic insertion and charge interaction, we designed three JMD mutations. First, Lys447, Phe448, Gly449 were deleted (dKFG), as in experiments performed in vivo.16 Second, Phe448 was mutated to Ser448 (FS) to remove the favorable aromatic ring insertion. Third, Arg452 was substituted with Trp452 (RW) to replace charge interactions with hydrophobic interactions. The mutant systems were simulated with the same protocols as the WT. In dKFG and FS, the removal of membrane-associative residues Lys447 and Phe448, or the introduction of polar residue Ser448 eliminates insertion and leaves electrostatic anchoring alone. In RW, the loss of basic Arg452 is compensated by the introduced Trp452 insertion (Figure 4). As a result, in addition to FGI insertions, residues 452 – 456 are partially embedded within the membrane. RW mutation also induces more fluctuation than the native sequence. Similar binding patterns were observed for other membrane compositions (Figures S3, S4), and convergence is mostly achieved as different replicates yield similar boxplots (Figure S5).

Figure 4.

Figure 4.

Open in a new tab

Role of mutations on TrkA-JMD binding. (a) Insertion distance for dKFG, FS, RW mutants in PC/PS membrane. (b) Illustration of the surface functionalization and single-molecule imaging of specific bound peptide on vesicles immobilized on channel surface. (c) Fluorophore counts of Cy3-labeled peptides bound with different vesicles at peptide concentration equal to 1 μg/mL. Vesicle compositions: vesicle-1 100% DOPC, vesicle-2 65% DOPC and 35 % DOPS, vesicle-3 95% DOPC and 5% PIP2. Error bars denote 95% confidence interval.

To validate the computational findings, we used a single-molecule detection-based peptide-liposome binding assay to evaluate the binding affinity between DiD-labeled, composition-controlled lipids and Cy3-labeled JMD peptides (Figure 4b). Full coverage vesicles were prepared to eliminate non-specific interactions between peptides and the polyethylene glycol (PEG) coated surface. The peptide-vesicle binding affinity was directly proportional to the number of Cy3 fluorescent spots in a field of view. Enhanced peptide binding was seen in PC/PS and PC/PIP2 vesicles with 1 μg/mL of peptide. The number of detected spots increases from FS to WT to RW (Figure 4c), suggesting that the partition susceptibility of JMD binding to anionic membrane ranks as FS < WT < RW. This result agrees with the insertions predicted by MD simulations. From the count differences between vesicles, it can be concluded that long-range electrostatics promotes peptide binding. However, once the binding is achieved, the extent of hydrophobic insertion significantly affects the strength of binding. The PC-only membrane is likely too neutral for peptide to attach in the experiment, while the separation is small enough to allow peptide binding to PC membrane in the simulation.

TrkA-JMD conformation is distinct from experimentally3 and computationally6 characterized EGFRJMD conformations: EGFR-JMD forms a short but structured 9-residue helix from Leu679 to Glu687 that can be membrane-embedded, while the corresponding Ile450 to Pro458 residues in TrkA-JMD are disordered and suspended in water. The disordered structure is also supported by secondary structure prediction webservers.38,39 In the N-terminus, in addition to the strong electrostatic binding due to the conserved presence of basic residue, TrkA-JMD possesses stable hydrophobic insertion unseen in EGFRJMD. Even though HMMM is different from full-tail membrane, free energy changes of side-chains membrane insertion agree well among the two models.40 Interestingly, the experimental Wimley-White hydrophobicity scale41 gives similar predictions on the insertion profiles characterized by MD-HMMM simulations. The Wimley-White scale provides the free energy change of partitioning a whole residue into PC membrane using pentapeptide AcWL-X-LL, describing the tendency of X for membrane insertion. To avoid confusion, it is worth noting that basic residue association with anionic membrane is a different scenario and not expected to follow the positive free energies given by the scale.

To list the relevant residues, Phe and Trp have negative free energies of −1.13 and −1.85 kcal/mol, respectively. Ser, Pro, Ala, Val have positive free energies of 0.13, 0.45, 0.17, 0.07 kcal/mol, respectively, due to the unfavorable contribution from polar peptide bond. These free energy values are consistent with the following computational results: 1) in WT, Phe448 engages in stable insertion, yet residues after Arg452 do not; 2) FS mutation completely removes insertion; 3) RW mutation is highly favorable and compensate for the loss of basic-lipid interaction and even promotes insertion of additional residues. Though the Wimley-White scale is obtained for PC-only membrane, our simulations indicate similar patterns of insertion in anionic membranes. Altogether, in addition to previously characterized electrostatic binding between JMD and anionic membranes,7,10–13 our results suggest that hydrophobic insertions also contribute to the membrane anchoring and stabilization of N-terminal TrkA-JMD.

Electrostatic Interactions

To explore protein-lipid interaction as is evident from the membrane partitioning of N-terminus, contacts between lipid charged moieties and residues 440 – 452 were mapped. Mean contact number measures the average number of contacting lipids at a given frame. Mean contact number for the WT confirms that most contacts were formed with the basic residues (Figure 5a, see Figure S6 for mutants). Considering the amounts of lipids present are nearly equal, stronger charge interaction is formed in PC/PS, PC/PS/PIP2 membranes (on average two lipids per basic residue) than in the PC membrane (one lipid per basic residue). Mean contact duration measures the average time a lipid stays in contact with the residue side-chain before it dissociates. Mean contact duration for each type of lipid is calculated for the PC/PS/PIP2 membrane in contact with the WT (Figure 5b, see Figure S7 for mutants). The average binding time of PIP2 is on the order of tens of nanoseconds, in stark contrast to the short-lived contacts by PC and PS lipids.

Figure 5.

Figure 5.

Open in a new tab

Molecular characterization of JMD-lipid interactions. (a) Mean contact number for 3 membranes and 13 residues in the N-terminus of the WT JMD. (b) Mean contact duration for 3 types of lipids in PC/PS/PIP2 and 13 residues in the N-terminus of the WT JMD. (c) The fraction of contact pairs for acidic-basic and basic-basic contacts on wide-type and mutant JMD is presented as violin plot. Average value is calculated for each replicate in wild-type and mutant systems. The width of the violin is proportional to the number of data points. Quartiles are shown as dashed lines. (d) A snapshot of PIP2 inositol phosphates coordinating three JMD basic residues.

To address the role of differently charged lipids, we analyzed contacts formed between residues on JMD. The contacts were evaluated in fraction of contact pairs, the average occurrence of two-residue contacts divided by the number of possible pairs to be formed (Figure 5c). Particularly, contacts between any of acidic Glu459, Asp460 and any of the basic residues (vary in WT and mutants) are shown to be present in PC-only membrane, but not in the more charged membranes. Though considerable replicate-level variation exists as each violin plot contains only 20 data points, contacts between basic residues are more frequent in negatively charged membranes. In some replicates PIP2 is capable of coordinating more than two residues (Figure 5d).

In all three lipid compositions, JMD peptide rapidly forms an encounter complex with membrane from the initial position 20 Å away. This membrane attachment of JMD N-terminus through long-range charge-interaction is necessary for membrane insertion, as suggested by the vesicle-binding experiment. Although PS and PIP2 lipids exhibit enhanced charge interaction (Figure 5a), PS lipids tend to form frequent yet transient contacts, while PIP2 lipids persistently bind to basic residues (Figure 5b). With the addition of anionic lipids, fold-increase of basic-basic residue contacts in JMD is observed (Figure 5d). Combined with the contact analysis, the results point to a distinct mode of PIP2-peptide interactions where two phosphate groups on the inositol ring coordinate more than one basic residue for prolonged time (tens of nanoseconds).

The primary effect of membrane composition on TrkA-JMD conformation can be seen on the C-terminus where acidic residues reside. This region tends to be more flexible and distal from the membrane as the amount of anionic lipids increases (Figure 3a, 3a, S3, S4). One factor is the repulsion between acidic residues and enriched negative charge in the membrane. Another factor is the competition between anionic lipids and JMD acidic residues to bind basic residues. As more anionic lipids are included, acid-basic residue contacts that loop the C-terminus closer to the membrane get depleted (Figure 5d). This effect would be significant if the orientation of JMD C-terminus in turn affects the orientation of downstream kinase domain. The interplay between membrane composition and JMD orientation might potentially explain the relative conservation of acidic residues on the C-terminal patch of JMD in all RTKs.10

Full Receptor Function

Because TrkA-JMD is involved in NGF-mediated degradation,16 we hypothesize that mutations altering JMD-membrane interactions can affect in-cell degradation kinetics. To test this hypothesis, we transfected SH-SY5Y human neuronal cells with wild-type (WT) and mutant (FS, RW) hTrkA fused with a human influenza hemagglutinin tag (hTrkA-HA). Twenty-four hours after transfection, cells were starved in serum-free medium for 6 hours prior to treatment with nerve growth factor (NGF). Cycloheximide was applied 1 h before NGF treatment, and Western blot analysis against HA was used to monitor the intracellular level of TrkA. The abundance of WT- and FS-hTrkA-HA decreased to approximately 80% 180 min after NGF treatment (Figure 6a). The RW mutant, on the other hand, showed significantly faster degradation kinetics, as evidenced by the 50% pre-treatment level as short as 90 min after NGF treatment (Figure 6b). Variation of the hTrkA abundance should not arise from unequal loading because the level of the GAPDH (loading control) protein from the same blot were comparable between replicates. This result suggested that RW mutation accelerates the NGF-mediated degradation kinetics of hTrkA, given that an equal amount of WT and mutant hTrkA was transfected.

Figure 6.

Figure 6.

Open in a new tab

Quantitative determination of the degradation kinetics and signaling activity for the WT, FS, and RW HA-hTrkA mutants in SHSY5Y cells. (a) Western blot analysis of TrkA abundance probed with an anti-HA antibody. Serum-deprived cells were pre-treated with cycloheximide to block new protein synthesis, followed by 100 ng/mL NGF treatment for 0, 10, 90, and 180 min. GAPDH was used as a loading control. (b) Quantification of the TrkA level normalized over GAPDH level from three replicates. The RW mutant shows significantly faster degradation kinetics than the WT and FS mutants. (c) Western blot analysis of the NGF-mediated ERK signaling activation in SHSY5Y cells. Cells were treated the same as in a). (d) Quantification of the pERK level normalized over GAPDH level from three replicates. No significant difference was detected between WT and two TrkA mutants.

Endocytosis of TrkA that results in endosome degradation or receptor recycling is triggered by NGF-induced ubiquitination performed by multiple E3 ligases.42–44 Lys447 is mono-ubiquitinated and its deletion causes resistance to degradation.16,44 Our insertion analysis shows that Lys447 is membrane inserted for half of the simulation time in the WT and RW (likely driven by Phe448), but is free in the FS. Intriguingly, our in-cell results suggest the level of ubiquitination in the FS is similar to that in the WT (Figure 6b), even though in the FS mutant, Lys447 is more exposed to solvent. The finding that RW mutation promotes ubiquitination is subject to at least two explanations: 1) the insertion profile of residues downstream Lys447 affects substrate recognition of the E3 ligase, likely Cbl-b;44 2) since ubiquitination occurs after receptor activation, the active JMD conformation is altered by RW mutation but differs from our computational prediction of free JMD. This finding may guide future studies that probe the TrkA conformational change upon activation.

Prior studies suggest that JMDs in EGFR and FGFR3 can switch from membrane-embedded state to free-floating state depending on TMD dimer tilt angles.5–7 Inspired by these findings, we hypothesize that the mutant FS and RW will change inherent TrkA activity by reducing and enhancing JMD binding affinity to the membrane, shifting the equilibrium to favor one state. Prior experiments showed that the dKFG mutation induces more robust signaling,16 which correlates with our hypothesis and computational observation of altered membrane insertion (Figure 4a). However, after NGF binding activates downstream Ras/ERK (extracellular signal regulated kinase) pathway, the FS and RW mutants show similar fold increases of pERK activity as the WT (Figure 6c–d). To account for background noise from indigenous TrkA in SH-SY5Y cell-line, we repeat in HEK293T cell-line that does not express indigenous TrkA or degradation machinery. The data confirms that the difference in the signaling capacity of WT/FS/RW-TrkA cannot be resolved from noise (Figure S11). Although here we computationally reported the behavior of truncated TrkA-JMD, in-cell experiments suggest the role of JMD in full receptor can be more involved and requires further investigation.

Conclusion

Using all-atom molecular dynamics, we highlighted the roles of hydrophobic and electrostatic binding in peptide-membrane interactions. We recovered the strong charge-driven interactions between anionic lipids and basic residues in TrkA-JMD N-terminus, previously emphasized by coarse-grained studies. With increased concentrations of PS and PIP2 lipids, higher lipid contact number is observed. We also found PIP2 engages in stable binding (tens of nanoseconds) to two or more basic residues. As the PIP2 becomes enriched in membrane, this lipid-protein interaction diminishes salt-bridges in TrkA-JMD that are responsible for placing the C-terminus adjacent to membrane. In full-length receptor, the C-terminus is attached to the kinase domain, and reorientation of the kinase domain activates autophosphorylation. For these facts, we proposed that anionic lipids can potentially affect signaling activity by pushing off the C-terminus, and reorienting the JMD to form a larger angle with respect to the membrane plane.

In addition to electrostatic interactions, we characterized the TrkA-JMD insertion profiles, which agree with the experimental Wimley&White hydrophobicity scale. We revealed a highly stable F-G-I insertion in the JMD N-terminus. Substituting the Phenylalanine with Serine abolishes insertion, while replacing an Arginine to Tryptophan results in more insertions. Vesicle-binding experiment supported computational predictions, and showed that hydrophobic insertion is comparable to electrostatic binding in membrane association. The results suggested a peptide-membrane binding strategy where long-range electrostatics brings the domain near membrane for favorable hydrophobic patch to hook to it. Studies on EGFR and FGFR3 activation mechanism assigned different levels of JMD insertion to active/inactive states. We then hypothesized that perturbations on JMD insertion should change the inherent receptor response to ligand. However, biochemical assays on cell-lines with mutated human TrkA only showed differences in ubiquitination activity, but not in signaling capacity. This evidence indicates TrkA-JMD assumes a more convoluted role in signaling. Further studies should incorporate the effect of TMD, kinase domain and dimerization, in order to better elucidate the structural basis of receptor activation.

Supplementary Material

SI

Table 1.

TrkA-JMD Sequences

WT N-K-C-G-R-R-N-K-F-G-I-N-R-P-A-V-L-A-P-E-D-G-L-A-M-S
dKFG N-K-C-G-R-R-N-I-N-R-P-A-V-L-A-P-E-D-G-L-A-M-S
FS N-K-C-G-R-R-N-K-S-G-I-N-R-P-A-V-L-A-P-E-D-G-L-A-M-S
RW N-K-C-G-R-R-N-K-F-G-I-N-W-P-A-V-L-A-P-E-D-G-L-A-M-S
Open in a new tab

Table 2.

Vesicle Compositions

DOPC (mol%) DOPS (mol%) PIP2 (mol%) Biotin-PE (mol%)
Vesicle 1 99.8 0 0 0.2
Vesicle 2 64.8 35 0 0.2
Vesicle 3 94.8 0 5 0.2
Open in a new tab

ACKNOWLEDGMENT

T. V. P. acknowledges support from the Department of Chemistry, the School of Chemical Sciences, and the Office of the Vice-Chancellor for Research (RSOCR Award 4703) at University of Illinois at Urbana-Champaign. T. V. P. acknowledges computational resources from the Texas Advanced Computing Center (TACC) at the University of Texas at Austin made available from the Extreme Science and Engineering Discovery Environment (XSEDE) Grant TG-MCB130112, which is supported by National Science Foundation Grant ACI-1053575. K. Z. acknowledges support from the School of Molecular and Cellular Biology at UIUC and NIH (1R01GM132438). J.D. acknowledges support from NIH (R35GM128837). Z. W. acknowledges support from Student Pushing Innovation (SPIN) Program of the National Center for Supercomputing Applications (NCSA). Authors are grateful to Dr. Yekaterina (Katka) Golubeva for assistance with the RTK schematics.

Footnotes

Supporting Information. Supporting information contains supplementary methods, supplementary tables, and supplementary figures.

The authors declare no competing financial interests.

REFERENCES

  • (1).Lemmon MA; Schlessinger J Cell Signaling by Receptor-Tyrosine Kinases. Cell 2010, 141 (7), 1117–1134. 10.1016/j.cell.2010.06.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (2).Zhou R; Han B; Xia C; Zhuang X Membrane-Associated Periodic Skeleton Is a Signaling Platform for RTK Transactivation in Neurons. Science 2019, 365 (6456), 929–934. 10.1126/science.aaw5937. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (3).Jura N; Endres NF; Engel K; Deindl S; Das R; Lamers MH; Wemmer DE; Zhang X; Kuriyan J Mechanism for Activation of the EGF Receptor Catalytic Domain by the Juxtamembrane Segment. Cell 2009, 137 (7), 1293–1307. 10.1016/j.cell.2009.04.025. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (4).He L; Hristova K Consequences of Replacing EGFR Juxtamembrane Domain with an Unstructured Sequence. Sci. Rep 2012, 2, 854 10.1038/srep00854. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (5).Endres NF; Das R; Smith AW; Arkhipov A; Kovacs E; Huang Y; Pelton JG; Shan Y; Shaw DE; Wemmer DE; et al. Conformational Coupling across the Plasma Membrane in Activation of the EGF Receptor. Cell 2013, 152 (3), 543–556. 10.1016/j.cell.2012.12.032. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (6).Arkhipov A; Shan Y; Das R; Endres NF; Eastwood MP; Wemmer DE; Kuriyan J; Shaw DE Architecture and Membrane Interactions of the EGF Receptor. Cell 2013, 152 (3), 557–569. 10.1016/j.cell.2012.12.030. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (7).Tamagaki H; Furukawa Y; Yamaguchi R; Hojo H; Aimoto S; Smith SO; Sato T Coupling of Transmembrane Helix Orientation to Membrane Release of the Juxtamembrane Region in FGFR3. Biochemistry 2014, 53 (30), 5000–5007. 10.1021/bi500327q. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (8).Sarabipour S; Hristova K FGFR3 Unliganded Dimer Stabilization by the Juxtamembrane Domain. J. Mol. Biol 2014, 427 (8), 1705–1714. 10.1016/j.jmb.2015.02.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (9).Sengupta P; Bosis E; Nachliel E; Gutman M; Smith SO; Mihályné G; Zaitseva I; McLaughlin S EGFR Juxtamembrane Domain, Membranes, and Calmodulin: Kinetics of Their Interaction. Biophys. J 2009, 96 (12), 4887–4895. 10.1016/j.bpj.2009.03.027. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (10).Hedger G; Sansom MSP; Koldsø H The Juxtamembrane Regions of Human Receptor Tyrosine Kinases Exhibit Conserved Interaction Sites with Anionic Lipids. Sci. Rep 2015, 5, 9198 10.1038/srep09198. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (11).Halim KBA; Koldsø H; Sansom MSP Interactions of the EGFR Juxtamembrane Domain with PIP2-Containing Lipid Bilayers: Insights from Multiscale Molecular Dynamics Simulations. Biochim. Biophys. Acta 2015, 1850 (5), 1017–1025. 10.1016/j.bbagen.2014.09.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (12).Chavent M; Karia D; Kalli AC; Domański J; Duncan AL; Hedger G; Stansfeld PJ; Seiradake E; Jones EY; Sansom MSP Interactions of the EphA2 Kinase Domain with PIPs in Membranes: Implications for Receptor Function. Structure 2018, 26 (7), 1025–1034. 10.1016/j.str.2018.05.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (13).McLaughlin S; Smith SO; Hayman MJ; Murray D An Electrostatic Engine Model for Autoinhibition and Activation of the Epidermal Growth Factor Receptor (EGFR/ErbB) Family. J. Gen. Physiol 2005, 126 (1), 41–53. 10.1085/jgp.200509274. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (14).Michailidis IE; Rusinova R; Georgakopoulos A; Chen Y; Iyengar R; Robakis NK; Logothetis DE; Baki L Phosphatidylinositol-4,5-Bisphosphate Regulates Epidermal Growth Factor Receptor Activation. Pflugers Arch. Eur. J. Physiol 2011, 461 (3), 387–397. 10.1007/s00424-010-0904-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (15).Huang EJ; Reichardt LF Trk Receptors: Roles in Neuronal Signal Transduction. Annu. Rev. Biochem 2003, 72 (1), 609–642. 10.1146/annurev.biochem.72.121801.161629. [DOI] [PubMed] [Google Scholar]
  • (16).Kiris E; Wang T; Yanpallewar S; Dorsey SG; Becker J; Bavari S; Palko ME; Coppola V; Tessarollo L TrkA in Vivo Function Is Negatively Regulated by Ubiquitination. J. Neurosci 2014, 34 (11), 4090–4098. 10.1523/JNEUROSCI.4294-13.2014. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (17).Ohkubo YZ; Pogorelov TV; Arcario MJ; Christensen GA; Tajkhorshid E Accelerating Membrane Insertion of Peripheral Proteins with a Novel Membrane Mimetic Model. Biophys. J 2012, 102 (9), 2130–2139. 10.1016/j.bpj.2012.03.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (18).Vermaas JV; Baylon JL; Arcario MJ; Muller MP; Wu Z; Pogorelov TV; Tajkhorshid E Efficient Exploration of Membrane-Associated Phenomena at Atomic Resolution. J. Membr. Biol 2015, 248 (3), 563–582. 10.1007/s00232-015-9806-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (19).Baylon JL; Vermaas JV; Muller MP; Arcario MJ; Pogorelov TV; Tajkhorshid E Atomic-Level Description of Protein-Lipid Interactions Using an Accelerated Membrane Model. Biochim. Biophys. Acta - Biomembr 2016. 10.1016/j.bbamem.2016.02.027. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (20).The Uniprot Consortium. UniProt: A Worldwide Hub of Protein Knowledge. Nucleic Acids Res. 2019, 47, 506–515. 10.1093/nar/gky1049. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (21).Hanwell MD; Curtis DE; Lonie DC; Vandermeerschd T; Zurek E; Hutchison GR Avogadro: An Advanced Semantic Chemical Editor, Visualization, and Analysis Platform. J. Cheminform 2012, 4, 17 10.1186/1758-2946-4-17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (22).Jo S; Kim T; Iyer VG; Im W CHARMM-GUI: A Web-Based Graphical User Interface for CHARMM. J. Comput. Chem 2008, 29, 1859–1865. 10.1002/jcc.20945. [DOI] [PubMed] [Google Scholar]
  • (23).Qi Y; Cheng X; Lee J; Vermaas JV; Pogorelov TV; Tajkhorshid E; Park S; Klauda JB; Im W CHARMM-GUI HMMM Builder for Membrane Simulations with the Highly Mobile Membrane-Mimetic Model. Biophys. J 2015, 109 (10), 2012–2022. 10.1016/j.bpj.2015.10.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (24).Van Meer G; Voelker DR; Feigenson GW Membrane Lipids: Where They Are and How They Behave. Nat. Rev. Mol. Cell Biol 2008, 9 (2), 112–114. 10.1038/nrm2330. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (25).Zachowski A Phospholipids in Animal Eukaryotic Membranes: Transverse Asymmetry and Movement. Biochem. J 1993, 294, 1–14. 10.1042/bj2940001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (26).Phillips JC; Braun R; Wang W; Gumbart J; Tajkhorshid E; Villa E; Chipot C; Skeel RD; Kalé L; Schulten K Scalable Molecular Dynamics with NAMD. J. Comput. Chem 2005, 26 (16), 1781–1802. 10.1002/jcc.20289. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (27).Huang J; Rauscher S; Nawrocki G; Ran T; Feig M; De Groot BL; Grubmüller H; MacKerell AD CHARMM36m: An Improved Force Field for Folded and Intrinsically Disordered Proteins. Nat. Methods 2016, 14, 71–73. 10.1038/nmeth.4067. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (28).Jorgensen WL; Chandrasekhar J; Madura JD; Impey RW; Klein ML Comparison of Simple Potential Functions for Simulating Liquid Water. J. Chem. Phys 1983, 79 (2), 926 10.1063/1.445869. [DOI] [Google Scholar]
  • (29).Vanommeslaeghev K, Hatcher E, Acharya C, Kundu S, Zhong S, Shim J, Darian E, Guvench O, Lopes P, Vorobyov I, Mackerell AD Jr. CHARMM General Force Field: A Force Field for Drug-Like Molecules Compatible with the CHARMM All-Atom Additive Biological Force Fields. J. Comput. Chem 2010, 31 (16), 2967–2970. 10.1002/jcc. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (30).Darden T; York D; Pedersen L Particle Mesh Ewald: An N·log(N) Method for Ewald Sums in Large Systems. J. Chem. Phys 1993. 10.1063/1.464397. [DOI] [Google Scholar]
  • (31).Essmann U; Perera L; Berkowitz ML; Darden T; Lee H; Pedersen LG A Smooth Particle Mesh Ewald Method. J. Chem. Phys 1995, 103, 8577 10.1063/1.470117. [DOI] [Google Scholar]
  • (32).Miyamoto S; Kollman PA Settle: An Analytical Version of the SHAKE and RATTLE Algorithm for Rigid Water Models. J. Comput. Chem 1992, 13 (8), 952–962. 10.1002/jcc.540130805. [DOI] [Google Scholar]
  • (33).Martyna GJ; Tobias DJ; Klein ML Constant Pressure Molecular Dynamics Algorithms. J. Chem. Phys 1994, 101 (5), 4177–4189. 10.1063/1.467468. [DOI] [Google Scholar]
  • (34).Humphrey W; Dalke A; Schulten K VMD: Visual Molecular Dynamics. J. Mol. Graph 1996, 14 (1), 33–38. 10.1016/0263-7855(96)00018-5. [DOI] [PubMed] [Google Scholar]
  • (35).Michaud-Agrawal N; Denning EJ; Woolf TB; Beckstein O MDAnalysis: A Toolkit for the Analysis of Molecular Dynamics Simulations. J. Comput. Chem 2011, 32 (10), 2319–2327. 10.1002/jcc.21787. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (36).Cai B; Yu L; Sharum SR; Zhang K; Diao J Single-Vesicle Measurement of Protein-Induced Membrane Tethering. Colloids Surfaces B Biointerfaces 2019, 177 (November 2018), 267–273. 10.1016/j.colsurfb.2019.02.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (37).Diao J; Ishitsuka Y; Lee H; Joo C; Su Z; Syed S; Shin YK; Yoon TY; Ha T A Single Vesicle-Vesicle Fusion Assay for in Vitro Studies of Snares and Accessory Proteins. Nat. Protoc 2012, 7 (5), 921–934. 10.1038/nprot.2012.020. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (38).Drozdetskiy A; Cole C; Procter J; Barton GJ JPred4: A Protein Secondary Structure Prediction Server. Nucleic Acids Res. 2015. 10.1093/nar/gkv332. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (39).Lin K; Simossis VA; Taylor WR; Heringa J A Simple and Fast Secondary Structure Prediction Method Using Hidden Neural Networks. Bioinformatics 2005. 10.1093/bioinformatics/bth487. [DOI] [PubMed] [Google Scholar]
  • (40).Pogorelov TV; Vermaas JV; Arcario MJ; Tajkhorshid E Partitioning of Amino Acids into a Model Membrane: Capturing the Interface. J. Phys. Chem. B 2014, 118 (6), 1481–1492. 10.1021/jp4089113. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • (41).Wimley WC; White SH Experimentally Determined Hydrophobicity Scale for Proteins at Membrane Interfaces. Nat. Struct. Biol 1996, 3 (10), 842–848. 10.1038/nsb1096-842. [DOI] [PubMed] [Google Scholar]
  • (42).Arévalo JC; Waite J; Rajagopal R; Beyna M; Chen ZY; Lee FS; Chao MV Cell Survival through Trk Neurotrophin Receptors Is Differentially Regulated by Ubiquitination. Neuron 2006, 50 (4), 549–559. 10.1016/j.neuron.2006.03.044. [DOI] [PubMed] [Google Scholar]
  • (43).Takahashi Y; Shimokawa N; Esmaeili-Mahani S; Morita A; Masuda H; Iwasaki T; Tamura J; Haglund K; Koibuchi N Ligand-Induced Downregulation of TrkA Is Partly Regulated through Ubiquitination by Cbl. FEBS Lett. 2011, 585 (12), 1741–1747. 10.1016/j.febslet.2011.04.056. [DOI] [PubMed] [Google Scholar]
  • (44).Emdal KB; Pedersen AK; Bekker-Jensen DB; Tsafou KP; Horn H; Lindner S; Schulte JH; Eggert A; Jensen LJ; Francavilla C; et al. Temporal Proteomics of NGF-TrkA Signaling Identifies an Inhibitory Role for the E3 Ligase Cbl-b in Neuroblastoma Cell Differentiation. Sci. Signal 2015, 8 (374), ra40 10.1126/scisignal.2005769. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

SI
NIHMS1570259-supplement-SI.pdf (1.9MB, pdf)

RESOURCES